Introduction to JupyterLab
- What is JupyterLab?
- How can you access it?
- Interface basics
- Resources
- Q & A
What is JupyterLab?
- Browser-based interactive environment
- Combines functional code, data exploration, and presentation in a
single portable file
- Supports Python, R, Julia, and more
- Ideal for data science, research, and teaching
JupyterLab: power of this, without all the clutter:
JupyterLab Launcher
Or if you prefer, much of this, less clutter:
JupyterLab Launcher
Vanilla out of the box, looks something like this:
JupyterLab Launcher
Where can you run Jupyter
Jupyter on Your Hardware
- Requires more setup effort
- Limited by your hardware, but keeps data local
- Example of launching local
Jupyter Cloud-Based Options
- Multiple platforms available:
- Google Colab
- Kaggle Notebooks
- Azure Notebooks
- Binder
- GitHub Codespaces
- JupyterHub (e.g., Titan Computing Hub)
Today we will focus on univeral tips for the common experience
- In the interest of time, lets all work from this jupyter lite
example: https://jupyter.org/try-jupyter/lab/
- jupyter lite is limited since it runs in a browswer sandbox
- requires no installation
- does not retain anything
JupyterLab Interface
- Menu Bar: File, Edit, View, Run options
- Left Sidebar: File browser, running kernels,
extensions
- Main Work Area: Notebooks, terminals, text
editors
Operations, Tips, and Shortcuts 1
- Create a notebook
- Open a notebook
- Create a Markdown cell
- Code Cell
- Run cells
Operations, Tips, and Shortcuts 2
- Markdown cell
- Use Command Mode and keyboard shortcuts
- [esc] -[a],[b],[x],[z],[m],[y]
Where to Go from Here
- Experiment with Jupyter to assess its value to your process -Explore
what your colleagues have already done: - CS
- Soc
- Time
Series
- Learn to install and use Jupyter locally
- Self-study via LinkedIn
Learning